Skills
101,174 packaged capabilities and playbooks for agents. Install any of them with one command.
All
Use when planning comprehensive Liquid Glass adoption across an app, auditing existing interfaces for Liquid Glass compatibility, implementing app icon updates, or understanding platform-specific Liquid Glass behavior — a comprehensive reference guide covering all aspects of Liquid Glass adoption from WWDC 2025
Expert knowledge for Azure AI Vision development including decision making, limits & quotas, configuration, integrations & coding patterns, and deployment. Use when using Image Analysis, Read OCR containers, smart-crop thumbnails, background removal, or video frame analysis, and other Azure AI Vision related development tasks. Not for Azure AI Custom Vision (use azure-custom-vision), Azure AI Video Indexer (use azure-video-indexer), Azure AI Document Intelligence (use azure-document-intelligence), Azure AI Immersive Reader (use azure-immersive-reader).
Guides all better-i18n integration decisions — SDK selection (Next.js, React, Expo, Swift, Flutter, Remix), CDN vs GitHub workflow, AI-powered translation management via MCP tools, CLI health checks (scan, doctor, sync), Content CMS (localized models, entries, custom fields), file format conventions (flat / nested / namespaced), key naming, publish flows, and quality analytics. Use whenever building, modifying, or reviewing any localization feature — including i18n setup, adding languages, managing translation keys, publishing, or integrating AI workflows
Build a vulnerability exception and risk acceptance tracking system covering approval workflows, compensating controls documentation, and automatic expiration for vulnerabilities that miss SLA remediation timelines. Use when standing up a governance process for risk acceptance and exception approvals to support PCI DSS, SOC 2, or NIST CSF compliance
Use when work must be verified in local Canvas Workbench, or when the user asks to run, open, check, or author component mocks or page previews in Workbench. Verifies that Canvas Workbench is available through the project's package runner, starts the local Workbench dev server, and keeps Workbench verification as part of the implementation workflow
Ultra-compressed communication mode. Cuts token usage by about 75% by speaking like a caveman while preserving full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when the user says “caveman mode,” “talk like caveman,” “use caveman,” “less tokens,” “be brief,” or invokes /caveman. Also auto-triggers when token efficiency is requested.
Go-to-market agent skills that turn a coding agent into a GTM operator: positioning + ICP, AI pricing, sales-motion design, cold outreach, AI SDR, lead enrichment, multi-platform and Product Hunt launches, programmatic SEO, paid creative, retention/expansion, partner programs, and GTM metrics/attribution.
Build elaborate multi-component claude.ai HTML artifacts with React, TypeScript, Vite, Tailwind CSS, and shadcn/ui, then bundle them into a single HTML file. This is the artifacts-builder skill from ComposioHQ's awesome-claude-skills collection, a copy of Anthropic's web-artifacts-builder. It does not integrate Composio tools.
Author continuously-running online evaluations in PostHog AI observability, grounded in real failure modes you've identified. Use when the user wants evaluations that automatically score new generations or whole traces going forward — "create an eval to catch X", "continuously check that responses do Y", "turn these failures into evals", or after reading traces finds a recurring failure. Covers letting the explored data decide how many evals to create, proposing that set for the user to pick, choosing the target and eval type (hog / llm_judge / sentiment), configuring an llm_judge's provider and model, scoping which generations trigger it via conditions, creating disabled, verifying scope, enabling, and backfilling past data. Proposes a sentiment eval when no failure mode is worth catching. Finding and ranking the failure modes worth evaluating is its own job — use exploring-ai-failures first. To debug or manage evaluations that already exist, use exploring-llm-evaluations.
Generate type scales, color palettes, spacing systems, WCAG contrast checks, and dark mode derivations with math. Use when setting up a design system, creating tokens, or building a Tailwind/CSS theme. Outputs CSS custom properties, Tailwind config, or JSON tokens.
Digital forensics and incident response - Windows event log analysis, PCAP forensics, filesystem artifact analysis, AD attack detection, and timeline correlation. Use when investigating security incidents, analyzing Sherlocks, or performing threat hunting on provided evidence files
Figma design bridge for Claude Code: browse Figma files through the figma-developer-mcp server, download assets, extract design tokens, and generate code for Tailwind, React, Vue, Svelte, React Native, Flutter and plain CSS. Also finds Figma Community resources that match the project. Needs a Figma access token and the figma-developer-mcp server.
AI-powered financial analysis suite. Generates executive CFO briefings from QuickBooks exports (P&L, Balance Sheet, General Ledger, Cash Flow, etc.) with anomaly detection, burn rate, runway analysis, and scenario modeling. Also estimates codebase development costs with organizational overhead and AI ROI analysis. Triggers on: 'CFO briefing', 'financial analysis', 'cost briefing', 'expense review', 'runway analysis', 'burn rate', 'cost estimate', 'how much would this cost to build', 'development cost', 'Claude ROI'.
Adversarially review an existing written artifact — stories, plans, acceptance criteria, specs, or design mocks — to surface missing states, unhandled edge cases, unstated assumptions, unverifiable criteria, and slices still too broad or horizontal. Works interactively, one question at a time, writing each answer back into the artifact as a new acceptance criterion, plan update, or mock-state spec. Use when an artifact needs tightening before planning or coding ("what's missing?", "poke holes in this", "tighten this up"). Requires an artifact to inspect — for a fuzzy decision tree with no artifact yet, use specification or an installed grill-me skill; for splitting oversized work, see story-splitting.
Build authority by teaching the problem space, not announcing features. Use when the user finds "marketing" distasteful and does none, publishes only product updates, or wants a sustainable content and GitHub-README strategy that developers actually respect.
Coach the user through actually selling: finding the champion and the buyer, running the first sales conversations, demoing their use case, handling “let me think about it,” and closing the first paying customers yourself. Use when developers love it but nobody pays, you've never sold anything and freeze during the conversation, or deals keep stalling on “we'll think about it.”
This skill should be used when a task requires designing or implementing frontend UI (components, pages, layouts, styling) and no more specialized frontend skill is a better fit. It guides production-grade, brand-consistent visual implementation with distinctive but controlled aesthetics.
Structured Git commit messages following Conventional Commits for Go projects. Generates well-scoped, atomic commits with clear descriptions. Use when committing changes, writing commit messages, preparing PRs, or reviewing commit history quality. Examples: “commit these changes,” “create commit,” “commit message,” “prepare PR,” “squash commits.” Not for code review (go-code-review) or changelog generation.
Systematic backlink building for indie founders. Covers 5 channel types ranked by GEO + SEO ROI: Wikipedia (entities), authoritative media (PR), industry reviews (G2/Capterra/Product Hunt), Reddit/Quora discussions, and HARO/Featured.com expert quotes. Designed for 0→1 sites where domain authority is the bottleneck. Aligns with 2026 Google/Bing GEO guidance: backlinks are the strongest brand-authority signal AI search engines use to decide citations. Defaults to dev/B2B link sources; for 2C products (education, consumer apps) authority links differ — see gingiris-seo-geo/references/2c-adaptation.md.
Refactors and reviews SwiftUI view files with strong defaults for small dedicated subviews, MV-over-MVVM data flow, stable view trees, explicit dependency injection, and correct Observation usage. Use when cleaning up a SwiftUI view, splitting long bodies, removing inline actions or side effects, reducing computed `some View` helpers, or standardizing `@Observable` and view model initialization patterns.
Provides an access guide for the Huawei Cloud Graph Database GES service. Covers Cypher queries, GQL queries, schema/label management, summary info queries, graph data editing, and more. Use this skill when users want to operate the Huawei Cloud graph database GES service via terminal.
Registers external HTTP endpoints as iii functions using registerFunction(id, HttpInvocationConfig). Use when adapting legacy APIs, third-party webhooks, or immutable services into triggerable iii functions, especially when prompts ask for endpoint maps like { path, id } iterated into registerFunction calls.
Registers a boolean condition function and attaches it to triggers via condition_function_id so handlers only fire when the condition passes. Use when gating triggers on business rules, checking user permissions, validating data before processing, filtering high-value orders, rate-limiting events, or conditionally skipping handlers based on payload content.
Implement and extend PostHog Data warehouse import sources. Use when adding a new source under products/warehouse_sources/backend/temporal/data_imports/sources, adding datasets or endpoints to an existing source, or adding incremental sync, resumable imports, webhook ingestion, pagination, credential validation, and source tests.
Create social media content optimized for Israeli audiences across Facebook, Instagram, TikTok, and LinkedIn. Use when user asks about Israeli social media strategy, Hebrew social posts, posting schedules for Israel, Hebrew hashtags, or Israeli Facebook group marketing. Covers platform-specific best practices, Israeli cultural references, and Hebrew copywriting for social. Do NOT use for paid ad campaigns, influencer outreach, or SEO content writing.
Comprehensive Java development best practices covering SOLID principles, DRY, Clean Code, Java-specific patterns (Optional, immutability, streams, lambdas), exception handling, collections, concurrency, testing with JUnit 5 and Mockito, code organization, performance optimization, and common anti-patterns. Essential reference for uncle-duke-java agent during code reviews and architecture guidance.
Discover and route Jinkō QSP and mechanistic-modeling requests to the public Jinkō skill that owns the work. Use when the user is starting a Jinkō session, asks what capability or skill to use, describes a multi-area modeling request, or has not yet identified the relevant jinko-* or jinko-task-* skill. This skill does not make scientific decisions, plan workflows, execute SDK calls, or decide that a task step is complete.
Explain core Jinkō context, navigation, version management, and domain language for agents and users. Use this skill whenever the user needs a mental model of Jinkō projects, folders, project items, snapshots, references, extracts, highlights, protocols, trials, calibration, virtual populations, traceability links, or modeling context; when translating between generic terms and Jinkō terminology; or when an agent needs orientation before navigating or modifying Jinkō artifacts. It includes a safe SDK example to list folders, render their tree, and create a folder after explicit user confirmation. Use dedicated jinko-* workflow skills for creating or editing scientific artifacts.
Build or edit a Jinkō computational model (QSP/PK-PD) via the jinko-sdk: parameters, categorical parameters, compartments, species, ODEs, reactions, dosing events, algebraic rules, baseline checks, solving options, units, and component tags. Use this skill whenever the user wants to create a model from scratch, create an empty model, edit an existing model, add or modify components, apply input/source/output tags, configure unit checking, define model-level dosing events, combine two models and resolve their conflicts, validate diagnostics, or debug model sanity or simple_solve errors. Prefer editing existing models over recreating them. Do not use this skill for running trials; use jinko-trial for trial execution.
The jinko-solution-and-product-guide skill provides users with clear, concise information about solutions (services capabilities) and product features in jinko to solve the users scientific and modeling objectives. Use this skill whenever you need guidance on finding models in the library to help get a fast start or understand jinko features to accelerate your integrated modeling strategy.
Create, sanity-check, run, poll, download results, and compute plot data for Jinkō in-silico trials via the jinko-sdk. Use this skill whenever the user wants to set up a trial from a computational model and simple output set, optionally attach a vpop, protocol, data table, or advanced scoring output set, launch a trial, wait for completion, inspect completed trials, download TimeSeries and Scalar results as pandas DataFrames, or get calculated plot data (scalar distributions, time-series quantile bands, survival curves, contribution/tornado analysis, per-patient scatter values), filtered or grouped by descriptors, to draw their own plots. Do not use this skill for model editing, vpop creation, protocol design authoring, data-table upload, output-set creation/editing, or configuring a stored TrialVisualization.
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.